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Scalable Machine Learning with Dask
http://ml.dask.org
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Dask ml LogisticRegression NotImplementedError: Could not find signature for add_intercept: <csr_matrix> #827

Open cs201503 opened 3 years ago

cs201503 commented 3 years ago

Hello, I am learning to use Dask ml to analyze data, here is part of my code: from dask_ml.linear_model import LogisticRegression lr = LogisticRegression(max_iter=1000) lr.fit(x_train_tfidf, y_train)

When I run it, the error appears:

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
~\anaconda3\lib\site-packages\multipledispatch\dispatcher.py in __call__(self, *args, **kwargs)
    268         try:
--> 269             func = self._cache[types]
    270         except KeyError:

KeyError: (<class 'scipy.sparse.csr.csr_matrix'>,)

During handling of the above exception, another exception occurred:

NotImplementedError                       Traceback (most recent call last)
<timed exec> in <module>

~\anaconda3\lib\site-packages\dask_ml\linear_model\glm.py in fit(self, X, y)
    181         self : objectj
    182         """
--> 183         X = self._check_array(X)
    184 
    185         solver_kwargs = self._get_solver_kwargs()

~\anaconda3\lib\site-packages\dask_ml\linear_model\glm.py in _check_array(self, X)
    195     def _check_array(self, X):
    196         if self.fit_intercept:
--> 197             X = add_intercept(X)
    198 
    199         return check_array(X, accept_unknown_chunks=True)

~\anaconda3\lib\site-packages\multipledispatch\dispatcher.py in __call__(self, *args, **kwargs)
    271             func = self.dispatch(*types)
    272             if not func:
--> 273                 raise NotImplementedError(
    274                     'Could not find signature for %s: <%s>' %
    275                     (self.name, str_signature(types)))

NotImplementedError: Could not find signature for add_intercept: <csr_matrix>

I would appreciate if someone can help me. Thank you!

jsignell commented 3 years ago

It looks like something is wrong with your environment. Can you confirm that you have scipy installed? You can dump your whole environment by doing conda list

cs201503 commented 3 years ago

It looks like something is wrong with your environment. Can you confirm that you have scipy installed? You can dump your whole environment by doing conda list

Hi Julia, thank you for replying, yes I have scipy installed, the whole environment is as follows:

Name Version Build Channel

_ipyw_jlab_nb_ext_conf 0.1.0 py38_0 _r-mutex 1.0.0 anacondar_1 absl-py 0.12.0 pypi_0 pypi aiohttp 3.7.3 py38h294d835_0 conda-forge aiohttp-cors 0.7.0 pypi_0 pypi aioredis 1.3.1 pypi_0 pypi alabaster 0.7.12 py_0 anaconda 2020.07 py38_0 anaconda-client 1.7.2 py38_0 anaconda-navigator 1.9.12 py38_0 anaconda-project 0.8.4 py_0 argh 0.26.2 py38_0 asn1crypto 1.3.0 py38_0 astroid 2.4.2 py38_0 astropy 4.0.1.post1 py38he774522_1 astunparse 1.6.3 pypi_0 pypi async-timeout 3.0.1 py_1000 conda-forge atomicwrites 1.4.0 py_0 attrs 19.3.0 py_0 autopep8 1.5.3 py_0 babel 2.8.0 py_0 backcall 0.2.0 py_0 backports 1.0 py_2 backports.functools_lru_cache 1.6.1 py_0 backports.shutil_get_terminal_size 1.0.0 py38_2 backports.tempfile 1.0 py_1 backports.weakref 1.0.post1 py_1 bcrypt 3.1.7 py38he774522_1 beautifulsoup4 4.9.1 py38_0 bitarray 1.4.0 py38he774522_0 bkcharts 0.2 py38_0 blas 1.0 mkl bleach 3.1.5 py_0 blessings 1.7 pypi_0 pypi blosc 1.19.0 h7bd577a_0 bokeh 2.1.1 py38_0 boto 2.49.0 py38_0 boto3 1.16.25 pyhd8ed1ab_0 conda-forge botocore 1.19.25 pyhd8ed1ab_0 conda-forge bottleneck 1.3.2 py38h2a96729_1 brotlipy 0.7.0 py38he774522_1000 bzip2 1.0.8 he774522_0 ca-certificates 2020.6.24 0 anaconda cachetools 4.2.0 pypi_0 pypi certifi 2020.6.20 py38_0 anaconda cffi 1.14.0 py38h7a1dbc1_0 chardet 3.0.4 py38_1003 click 7.1.2 py_0 cloudpickle 1.5.0 py_0 clyent 1.2.2 py38_1 colorama 0.4.3 py_0 colorcet 2.0.2 py_0 pyviz colorful 0.5.4 pypi_0 pypi comtypes 1.1.7 py38_1001 conda 4.9.2 py38haa244fe_0 conda-forge conda-build 3.18.11 py38_1 conda-env 2.6.0 1 conda-package-handling 1.6.1 py38h62dcd97_0 conda-verify 3.4.2 py_1 console_shortcut 0.1.1 4 contextlib2 0.6.0.post1 py_0 cryptography 2.9.2 py38h7a1dbc1_0 curl 7.71.1 h2a8f88b_1 cycler 0.10.0 py38_0 cython 0.29.21 py38ha925a31_0 cytoolz 0.10.1 py38he774522_0 dask 2.20.0 py_0 dask-core 2.20.0 py_0 dask-glm 0.2.0 py_1 conda-forge dask-labextension 3.0.0 py_0 conda-forge dask-ml 1.7.0 py_0 conda-forge decorator 4.4.2 py_0 defusedxml 0.6.0 py_0 diff-match-patch 20200713 py_0 distributed 2.20.0 py38_0 docutils 0.16 py38_1 entrypoints 0.3 py38_0 et_xmlfile 1.0.1 py_1001 fastcache 1.1.0 py38he774522_0 filelock 3.0.12 py_0 flake8 3.8.3 py_0 flask 1.1.2 py_0 flatbuffers 1.12 pypi_0 pypi freetype 2.10.2 hd328e21_0 fsspec 0.7.4 py_0 future 0.18.2 py38_1 gast 0.3.3 pypi_0 pypi get_terminal_size 1.0.0 h38e98db_0 gevent 20.6.2 py38he774522_0 glob2 0.7 py_0 gmpy2 2.0.8 py38h7edee0f_3 google-api-core 1.25.0 pypi_0 pypi google-auth 1.24.0 pypi_0 pypi google-auth-oauthlib 0.4.3 pypi_0 pypi google-pasta 0.2.0 pypi_0 pypi googleapis-common-protos 1.52.0 pypi_0 pypi gpustat 0.6.0 pypi_0 pypi graphviz 2.38 hfd603c8_2 anaconda greenlet 0.4.16 py38he774522_0 grpcio 1.32.0 pypi_0 pypi h5py 2.10.0 py38h5e291fa_0 hdf5 1.10.4 h7ebc959_0 heapdict 1.0.1 py_0 hiredis 1.1.0 pypi_0 pypi holoviews 1.14.1 py_0 pyviz html5lib 1.1 py_0 icc_rt 2019.0.0 h0cc432a_1 icu 58.2 ha925a31_3 idna 2.10 py_0 imageio 2.9.0 py_0 imagesize 1.2.0 py_0 importlib-metadata 1.7.0 py38_0 importlib_metadata 1.7.0 0 intel-openmp 2020.1 216 intervaltree 3.0.2 py_1 ipykernel 5.3.2 py38h5ca1d4c_0 ipython 7.16.1 py38h5ca1d4c_0 ipython_genutils 0.2.0 py38_0 ipywidgets 7.5.1 py_0 isort 4.3.21 py38_0 itsdangerous 1.1.0 py_0 jdcal 1.4.1 py_0 jedi 0.17.1 py38_0 jinja2 2.11.2 py_0 jmespath 0.10.0 pyh9f0ad1d_0 conda-forge joblib 0.16.0 py_0 jpeg 9b hb83a4c4_2 json5 0.9.5 py_0 jsonschema 3.2.0 py38_0 jupyter 1.0.0 py38_7 jupyter-server-proxy 1.5.0 py_0 conda-forge jupyter_client 6.1.6 py_0 jupyter_console 6.1.0 py_0 jupyter_core 4.6.3 py38_0 jupyterlab 2.1.5 py_0 jupyterlab_server 1.2.0 py_0 keras-preprocessing 1.1.2 pypi_0 pypi keyring 21.2.1 py38_0 kiwisolver 1.2.0 py38h74a9793_0 krb5 1.18.2 hc04afaa_0 lazy-object-proxy 1.4.3 py38he774522_0 libarchive 3.4.2 h5e25573_0 libcurl 7.71.1 h2a8f88b_1 libiconv 1.15 h1df5818_7 liblief 0.10.1 ha925a31_0 libllvm9 9.0.1 h21ff451_0 libpng 1.6.37 h2a8f88b_0 libsodium 1.0.18 h62dcd97_0 libspatialindex 1.9.3 h33f27b4_0 libssh2 1.9.0 h7a1dbc1_1 libtiff 4.1.0 h56a325e_1 libxml2 2.9.10 h464c3ec_1 libxslt 1.1.34 he774522_0 llvmlite 0.33.0 py38ha925a31_0 locket 0.2.0 py38_1 lxml 4.5.2 py38h1350720_0 lz4-c 1.9.2 h62dcd97_0 lzo 2.10 he774522_2 m2w64-bwidget 1.9.10 2 m2w64-bzip2 1.0.6 6 m2w64-expat 2.1.1 2 m2w64-fftw 3.3.4 6 m2w64-flac 1.3.1 3 m2w64-gcc-libgfortran 5.3.0 6 m2w64-gcc-libs 5.3.0 7 m2w64-gcc-libs-core 5.3.0 7 m2w64-gettext 0.19.7 2 m2w64-gmp 6.1.0 2 m2w64-gsl 2.1 2 m2w64-libiconv 1.14 6 m2w64-libjpeg-turbo 1.4.2 3 m2w64-libogg 1.3.2 3 m2w64-libpng 1.6.21 2 m2w64-libsndfile 1.0.26 2 m2w64-libsodium 1.0.10 2 m2w64-libtiff 4.0.6 2 m2w64-libvorbis 1.3.5 2 m2w64-libwinpthread-git 5.0.0.4634.697f757 2 m2w64-libxml2 2.9.3 4 m2w64-mpfr 3.1.4 4 m2w64-openblas 0.2.19 1 m2w64-pcre 8.38 2 m2w64-speex 1.2rc2 3 m2w64-speexdsp 1.2rc3 3 m2w64-tcl 8.6.5 3 m2w64-tk 8.6.5 3 m2w64-tktable 2.10 5 m2w64-wineditline 2.101 5 m2w64-xz 5.2.2 2 m2w64-zeromq 4.1.4 2 m2w64-zlib 1.2.8 10 markdown 3.3.3 py38haa95532_0 markupsafe 1.1.1 py38he774522_0 matplotlib 3.2.2 0 matplotlib-base 3.2.2 py38h64f37c6_0 mccabe 0.6.1 py38_1 menuinst 1.4.16 py38he774522_1 mistune 0.8.4 py38he774522_1000 mkl 2020.1 216 mkl-service 2.3.0 py38hb782905_0 mkl_fft 1.1.0 py38h45dec08_0 mkl_random 1.1.1 py38h47e9c7a_0 mock 4.0.2 py_0 more-itertools 8.4.0 py_0 mpc 1.1.0 h7edee0f_1 mpfr 4.0.2 h62dcd97_1 mpir 3.0.0 hec2e145_1 mpmath 1.1.0 py38_0 msgpack-python 1.0.0 py38h74a9793_1 msys2-conda-epoch 20160418 1 multidict 4.7.5 py38h1e8a9f7_2 conda-forge multipledispatch 0.6.0 py38_0 navigator-updater 0.2.1 py38_0 nbconvert 5.6.1 py38_0 nbformat 5.0.7 py_0 networkx 2.4 py_1 nltk 3.5 py_0 nose 1.3.7 py38_2 notebook 6.0.3 py38_0 numba 0.50.1 py38h47e9c7a_0 numexpr 2.7.1 py38h25d0782_0 numpy 1.19.5 pypi_0 pypi numpydoc 1.1.0 py_0 nvidia-ml-py3 7.352.0 pypi_0 pypi oauthlib 3.1.0 pypi_0 pypi olefile 0.46 py_0 opencensus 0.7.12 pypi_0 pypi opencensus-context 0.1.2 pypi_0 pypi openpyxl 3.0.4 py_0 openssl 1.1.1g he774522_0 conda-forge opt-einsum 3.3.0 pypi_0 pypi packaging 20.4 py_0 pandas 1.1.4 pypi_0 pypi pandoc 2.10 0 pandocfilters 1.4.2 py38_1 panel 0.9.7 py_0 pyviz param 1.10.1 py_0 pyviz paramiko 2.7.1 py_0 parso 0.7.0 py_0 partd 1.1.0 py_0 path 13.1.0 py38_0 path.py 12.4.0 0 pathlib2 2.3.5 py38_0 pathtools 0.1.2 py_1 patsy 0.5.1 py38_0 pep8 1.7.1 py38_0 pexpect 4.8.0 py38_0 pickleshare 0.7.5 py38_1000 pillow 7.2.0 py38hcc1f983_0 pip 21.1 pypi_0 pypi pkginfo 1.5.0.1 py38_0 pluggy 0.13.1 py38_0 ply 3.11 py38_0 powershell_shortcut 0.0.1 3 prometheus_client 0.8.0 py_0 prompt-toolkit 3.0.5 py_0 prompt_toolkit 3.0.5 0 protobuf 3.14.0 pypi_0 pypi psutil 5.7.0 py38he774522_0 py 1.9.0 py_0 py-lief 0.10.1 py38ha925a31_0 py-spy 0.3.3 pypi_0 pypi py4j 0.10.9 pypi_0 pypi pyarrow 3.0.0 pypi_0 pypi pyasn1 0.4.8 pypi_0 pypi pyasn1-modules 0.2.8 pypi_0 pypi pycodestyle 2.6.0 py_0 pycosat 0.6.3 py38he774522_0 pycparser 2.20 py_2 pyct 0.4.8 py_0 pyviz pyct-core 0.4.8 py_0 pyviz pycurl 7.43.0.5 py38h7a1dbc1_0 pydocstyle 5.0.2 py_0 pydot 1.4.1 py38_0 anaconda pyflakes 2.2.0 py_0 pygments 2.6.1 py_0 pylint 2.5.3 py38_0 pynacl 1.4.0 py38h62dcd97_1 pyodbc 4.0.30 py38ha925a31_0 pyopenssl 19.1.0 py_1 pyparsing 2.4.7 py_0 pyqt 5.9.2 py38ha925a31_4 pyreadline 2.1 py38_1 pyrsistent 0.16.0 py38he774522_0 pysocks 1.7.1 py38_0 pyspark 3.0.2 pypi_0 pypi pytables 3.6.1 py38ha5be198_0 pytest 5.4.3 py38_0 python 3.8.3 he1778fa_2 python-dateutil 2.8.1 py_0 python-graphviz 0.14.2 py_0 anaconda python-jsonrpc-server 0.3.4 py_1 python-language-server 0.34.1 py38_0 python-libarchive-c 2.9 py_0 python_abi 3.8 1_cp38 conda-forge pytz 2020.1 py_0 pyviz_comms 0.7.6 py_0 pyviz pywavelets 1.1.1 py38he774522_0 pywin32 227 py38he774522_1 pywin32-ctypes 0.2.0 py38_1000 pywinpty 0.5.7 py38_0 pyyaml 5.3.1 py38he774522_1 pyzmq 19.0.1 py38ha925a31_1 qdarkstyle 2.8.1 py_0 qt 5.9.7 vc14h73c81de_0 qtawesome 0.7.2 py_0 qtconsole 4.7.5 py_0 qtpy 1.9.0 py_0 r-askpass 1.0 r36_0 r-assertthat 0.2.1 r36h6115d3f_0 r-backports 1.1.4 r36h6115d3f_0 r-base 3.6.1 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r36h6115d3f_0 r-gower 0.2.0 r36h6115d3f_0 r-gtable 0.3.0 r36h6115d3f_0 r-haven 2.1.0 r36h6115d3f_0 r-hexbin 1.27.2 r36h6115d3f_0 r-highr 0.8 r36h6115d3f_0 r-hms 0.4.2 r36h6115d3f_0 r-htmltools 0.3.6 r36h6115d3f_0 r-htmlwidgets 1.3 r36h6115d3f_0 r-httpuv 1.5.1 r36h6115d3f_0 r-httr 1.4.0 r36h6115d3f_0 r-ipred 0.9_8 r36h6115d3f_0 r-irdisplay 0.7.0 r36h6115d3f_0 r-irkernel 0.8.15 r36_0 r-iterators 1.0.10 r36h6115d3f_0 r-jsonlite 1.6 r36h6115d3f_0 r-kernsmooth 2.23_15 r36h6115d3f_4 r-knitr 1.22 r36h6115d3f_0 r-labeling 0.3 r36h6115d3f_4 r-later 0.8.0 r36h6115d3f_0 r-lattice 0.20_38 r36h6115d3f_0 r-lava 1.6.5 r36h6115d3f_0 r-lazyeval 0.2.2 r36h6115d3f_0 r-lubridate 1.7.4 r36h6115d3f_0 r-magrittr 1.5 r36h6115d3f_4 r-maps 3.3.0 r36h6115d3f_0 r-markdown 0.9 r36h6115d3f_0 r-mass 7.3_51.3 r36h6115d3f_0 r-matrix 1.2_17 r36h6115d3f_0 r-mgcv 1.8_28 r36h6115d3f_0 r-mime 0.6 r36h6115d3f_0 r-modelmetrics 1.2.2 r36h6115d3f_0 r-modelr 0.1.4 r36h6115d3f_0 r-munsell 0.5.0 r36h6115d3f_0 r-nlme 3.1_139 r36h6115d3f_0 r-nnet 7.3_12 r36h6115d3f_0 r-numderiv 2016.8_1 r36h6115d3f_0 r-openssl 1.3 r36h6115d3f_0 r-pbdzmq 0.3_3 r36h6115d3f_0 r-pillar 1.3.1 r36h6115d3f_0 r-pkgconfig 2.0.2 r36h6115d3f_0 r-plogr 0.2.0 r36h6115d3f_0 r-plyr 1.8.4 r36h6115d3f_0 r-prettyunits 1.0.2 r36h6115d3f_0 r-processx 3.3.0 r36h6115d3f_0 r-prodlim 2018.04.18 r36h6115d3f_0 r-progress 1.2.0 r36h6115d3f_0 r-promises 1.0.1 r36h6115d3f_0 r-ps 1.3.0 r36h6115d3f_0 r-purrr 0.3.2 r36h6115d3f_0 r-quantmod 0.4_14 r36h6115d3f_0 r-r6 2.4.0 r36h6115d3f_0 r-randomforest 4.6_14 r36h6115d3f_0 r-rbokeh 0.6.3 r36_0 r-rcolorbrewer 1.1_2 r36h6115d3f_0 r-rcpp 1.0.1 r36h6115d3f_0 r-rcpproll 0.3.0 r36h6115d3f_0 r-readr 1.3.1 r36h6115d3f_0 r-readxl 1.3.1 r36h6115d3f_0 r-recipes 0.1.5 r36h6115d3f_0 r-recommended 3.6.0 r36_0 r-rematch 1.0.1 r36h6115d3f_0 r-repr 0.19.2 r36h6115d3f_0 r-reprex 0.2.1 r36h6115d3f_0 r-reshape2 1.4.3 r36h6115d3f_0 r-rlang 0.3.4 r36h6115d3f_0 r-rmarkdown 1.12 r36h6115d3f_0 r-rpart 4.1_15 r36h6115d3f_0 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jsignell commented 3 years ago

It's hard to diagnose this without a reproducible example. It seems like your data may be a sparse matrix, which might be the issue. Can you include a subset of your data in the example?

Also I am moving this to the dask-ml issue tracker.

Abhishekdutt9 commented 2 years ago

Use lr.fit(x_train_tfidf.values, y_train.values) instead